code: def test_xdoc_featurize(self):
      model = SequenceLabeler(base_model=XDocBase)
      np.testing.assert_allclose(
          model.featurize_sequence(
              ["The quick brown fox jumped"],
              context=[
                  [
                      {
                          "left": 0,
                          "top": 0,
                          "right": 0,
                          "bottom": 0,
                          "start": 0,
                          "end": 26,
                      }
                  ]
              ],
          )[0],
          np.load(os.path.join(DIRECTORY, "data/xdoc_activations.npy"))[
              0, 1:-1
          ],
          atol=2e-3,
      )
  
file_path: finetune/tests/test_parity.py
imports: import unittest
  import os.path
  import pytest
  import numpy
  from tensorflow.data import Dataset
  from finetune.encoding.input_encoder import EncodedOutput
  from finetune.model import PredictMode
  from finetune.base_models import GPT, GPT2, BERT, RoBERTa, XDocBase
  from finetune import Classifier, MultiFieldClassifier, SequenceLabeler
label_desc: Use image node_id 7 for calling the TestActivationParity obj's underlying member method code with example usage: obj.test_xdoc_featurize() without return types